1. Field of the Invention
The present disclosure generally relates to video encoding, and, more particularly, is related to the reduction of noise for video encoding.
2. Related Art
With advancements in technology, significant advances have been made in video processing technology. Analog video processing, which provides limited compression through typical single scan-line or one-dimensional (“1-D”) processing, has been surpassed by more efficient multiple scan-line or two-dimensional (“2-D”) digital video processing. Two-dimensional digital video processing has been surpassed by horizontal, vertical and temporal or three-dimensional (“3-D”) digital video processing. Even MPEG-1, which was once the predominant mainstream 3-D video codec standard, has also recently been surpassed by the more versatile and higher-bit-rate-capable MPEG-2. Presently, MPEG-2 is the predominant mainstream compression standard.
As is known in the art, video recording is susceptible to different degrees and categories of noise that negatively affects video during compression and encoding. Samples of such noise include impulsive noise, such as, but not limited to, spikes, high contrast glitches, and “salt-n-pepper effect.” Another sample of such noise includes Gaussian-distributed white noise, such as, but not limited to, thermal noise and “snow,” which may arise from cable ingress, interference in an analog section of a digitizer utilized during video encoding, or other phenomena.
Not only does noise degrade picture quality directly by virtue of its visual appearance, but the presence of noise degrades the quality of compressed video indirectly because, as is known in the art, an appreciable fraction of bit rate is consumed to compress the noise. This leads to two situations. First, less bit rate is readily available to compress the real signal, resulting in increased compression impairments. Second, as is known in the art, compressed noise often has a more disturbing appearance than uncompressed noise. Thus, it is desirable to remove video noise prior to compression, particularly in situations where it is desired to minimize the bit rate.
Digital video noise can be removed by a variety of known digital processing techniques such as, but not limited to, finite impulse response (FIR) linear spatial filters, nonlinear spatial filters of various types, temporal filters, and even spatio-temporal filters. The temporal filter can take many forms, however, a typical temporal filter utilizes a motion-detector to moderate a recursive (infinite impulse response (IIR)) filter, which blends each pixel from a current image with a spatially co-located pixel from a previously filtered image. A large variety of noise reduction systems can be designed with different configurations of these basic components. Such noise reduction systems typically are set to operate in a static mode, in the sense that the noise characteristics are assumed not to change over time. The settings are set based on user input or based on offline (not real-time) measurements or calculations of the digital video noise. However, in a real environment, noise characteristics change over time or from video scene to video scene. Therefore, static noise reduction methods are insufficient, especially in systems such as consumer digital video recorders in which a user is not always present to control the recorder settings to compensate for changes in noise sources that may comprise widely varying noise characteristics.
Furthermore, without additional controls, the classical motion-detecting temporal filter with a simple motion detector has difficulty separating moving objects from noise, and thus cannot always use the best noise reduction setting. Specifically, in certain scenes, the classical motion-detecting temporal filter will filter too little, leaving more noise than necessary. Alternatively, in other scenes, the temporal filter may filter too much, visibly smearing moving objects or creating “ghosts,” which appear as attenuated copies of moving objects trailing behind objects as they move within a video.